Index: /issm/trunk-jpl/src/m/contrib/musselman/README.txt
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+The write_netCDF and read_netCDF modules provide a convenient way to save and restore the state of a model class instance 
+in binary format via NetCDF4. This allows users to store the class state on disk and retrieve it later, facilitating seamless 
+transitions between Python and MATLAB environments.
+
+To save a model, call either write_netCDF.py or write_netCDF.m depending on whether your class is in matlab or python. 
+To read a saved model, call either read_netCDF.py or read_netCDF.m depending on what language you prefer to use the model in.
+
+Usage Instructions:
+
+    Python:
+        - Saving a model: 
+            from write_netCDF import write_netCDF
+
+            md = bamg(model(), foo.csv, .01)
+
+            write_netCDF(md, 'md', 'adress_to_save/../filename.nc')
+
+        - Reading a model:
+            from read_netCDF import read_netCDF
+
+            md = read_netCDF('adress_to_file/../filename.nc')
+
+    MATLAB:
+        - Saving a model: 
+            import write_netCDF
+
+            write_netCDF(md, adress_to_save/../filename.nc)
+
+        - Reading a model:
+            import read_netCDF
+
+            md = read_netCDF(adress_to_file/../filename.nc)
+
+
+
+Dependencies:
+    Python: 
+        - NumPy 
+        - NetCDF4.Dataset
+        - The model() class
+
+    MATLAB: 
+        - The model() class
+
+
+Additional Information:
+
+There are currently datatypes that both write_netCDF and read_netCDF modules may not be able to handle. These datatypes might 
+include dictionaries with multiple value datatypes, lists with multiple datatypes, lists of dicts ect. 
+
+To add functionality for these additional cases, one must simply create a function to handle the case and call it using a 
+conditional case within the create_var() function. To read the data from the NetCDF4 file, add the case to the 
+copy_variable_data_to_new_model() function so that the data can be added to a new model() instance.